Journal
STATISTICS IN MEDICINE
Volume 21, Issue 13, Pages 1899-1911Publisher
WILEY
DOI: 10.1002/sim.1152
Keywords
panel data; stationary transition probabilities; Markov regression; goodness of fit; parametric bootstrap
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Markov regression models describe the way in which a categorical response variable changes over time for subjects with different explanatory variables. Frequently it is difficult to measure the response variable on equally spaced discrete time intervals. Here we propose a Pearson-type goodness-of-fit test for stationary Markov regression models fitted to panel data, A parametric bootstrap algorithm is used to study the distribution of the test statistic. The proposed technique is applied to examine the fit of a Markov regression model used to identify markers for disease progression in psoriatic arthritis. Copyright (C) 2002 John Wiley Sons, Ltd.
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